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Research >> EHRLL >> Brigham and Women's Hospital

Opioid Prescription Process, Brigham and Women's Hospital


The opioid epidemic is devastating the American public through loss of lives and financial burden. Although prescription opioids are contributing to the epidemic, patients using and providers prescribing the medicines are often chastised, even though many factors were brought into consideration before prescribing long term. This project is working to improve opioid prescribing processes, specifically for patients using opioids to treat chronic pain, at the Phyllis Jen Center for Primary Care within the Brigham and Women’s Hospital. Through use of systems engineering tools, the team aims to improve primary outcome measures related to safety, efficacy and efficiency of prescribing processes. Some examples include patient satisfaction and outcomes, provider burden and the accessibility of resources for all involved.


An interdisciplinary team of providers, licensed practicing nurses, pharmacists, public health experts, systems engineers and patients collaborated to apply systems engineering methods to processes associated with opioid prescribing. These methods – including process maps, run charts, failure modes effects analysis (FMEA), systems engineering initiative for patient safety (SEIPS), systematic theoretic process analysis (STPA), functional resonance analysis method (FRAM), and usability testing - were able to provide insight for identifying areas where the clinic was not providing adequate support for the staff and patients, leading to safety driven improvements that consider the system as a whole.


Process maps highlighted tasks that created inconsistencies in how processes were completed, guiding changes towards more reliable processes. Run charts illustrated the biggest areas for improvement of key performance indicators and helped assess the effectiveness of interventions. FMEA emphasized failures potentially most detrimental to patients, leading to more control actions being put in place to decrease the likelihood of those events. SEIPS made the system easy to understand on a macro level, and made it simple to identify components of the system that were not patient focused. FRAM analysis highlighted how variability in how tasks are completed can change outcomes, reinforcing the need for policies for certain processes. Usability testing made it so tools designed to help providers were intuitive and lead to adding features that providers found useful.

Partners & Research Team

Annie Shutt, HSyE

Malcolm Lord, HSyE

Alev Atalay, MD, BWH

Karen Sherritt, MD, BWH

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